Book Review: "The Responsibility to Understand: Hermeneutical Contours of Ethical Life" by Professor Theodore George
Bibliographic record
Abstract
This article is a review of Dr. Theodore George’s new book, The Responsibility to Understand: Hermeneutical Contours of Ethical Life (2020) from the viewpoint of applied hermeneutics and practice professions, especially nursing. I highlight aspects of the book that speak most directly to applied hermeneutics, including Figal’s version of objectivity, and the need to allow displacement to open space for new understanding. I discuss points that I think are open to continuing debate, including the question of whether hermeneutics is being presented as an ethics in itself, or as a gateway to ethical decision making that has to be determined by other values. For practice professions that are conspicuously bounded by regulations of various kinds, it is a feature of ethical life that has to be taken into account. Another question, is whether George’s analysis of solidarity, pushing back against impersonal, calculative values penetrating modern life, sufficiently captures the fervour of closed solidarities that have sprung up as reaction and adjunct to those same values. I suggest that George’s chapter on translation could provide a stimulating starting point for a hermeneutic analysis of “knowledge translation” in research. The conclusion is that George’s book is an excellent addition to the hermeneutic literature, post-Gadamer, that extends a welcome to those of us working in applied hermeneutics, inviting us into a thought provoking and creative conversation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.010 |
| Insufficient payload (model declined to judge) | 0.018 | 0.012 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".